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Found 3 papers, 2 papers with code
LVLane: Deep Learning for Lane Detection and Classification in Challenging Conditions
Experimental evaluations conducted on the widely-used TuSimple dataset, Caltech Lane dataset, and our LVLane dataset demonstrate the effectiveness of our model in accurately detecting and classifying lanes amidst challenging scenarios.
A Real-Time Wrong-Way Vehicle Detection Based on YOLO and Centroid Tracking
By detecting wrong-way vehicles, the number of accidents can be minimized and traffic jam can be reduced.
An enhanced method of initial cluster center selection for K-means algorithm
Clustering is one of the widely used techniques to find out patterns from a dataset that can be applied in different applications or analyses.
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